Precise Measurement of the e^{+}e^{-}→D_{s}^{+}D_{s}^{-} Cross Section at Center-of-Mass Energies from Threshold to 4.95 GeV.

Using the e^{+}e^{-} collision data collected with the BESIII detector operating at the BEPCII collider, at center-of-mass energies from the threshold to 4.95 GeV, we present precise measurements of the cross section for the process e^{+}e^{-}→D_{s}^{+}D_{s}^{-} using a single-tag method. The resulting cross section line shape exhibits several new structures, thereby offering an input for a future coupled-channel analysis and model tests, which are critical to understand vector charmonium-like states with masses between 4 and 5 GeV.

Case report: The case of T-cell acute lymphoblastic leukemia treated with chemotherapy followed by anti-CD7 CAR-T cells using retroviral vector.

CD7-targeted chimeric antigen receptor-T (CAR-T) cell therapy has shown great promise in the treatment of relapsed/refractory T-cell acute lymphoblastic leukemia (T-ALL). In this study, we reported a case of a 34-year-old male patient with T-ALL who finally developed multi-line drug resistance and refractoriness after multiple lines of high-intensity chemotherapy. After physician evaluation, this patient received allogeneic hematopoietic stem cell transplantation (allo-HSCT).

Neutralizing antibody landscape of the non-polio Enteroviruses and future strategy.

The non-polio Enteroviruses (NPEVs), consist of enteroviruses, coxsackieviruses, echoviruses, and rhinoviruses, are causative agents for a wide variety of diseases, ranging from common cold to encephalitis and acute flaccid paralysis (AFP). In recent years, several NPEVs have become serious public health threats, include EV-A71, which has caused epidemics of hand-foot-and-mouth disease (HMFD) in Southeast Asia, and EV-D68, which caused outbreaks of severe respiratory disease in children worldwide. Infections with these viruses are associated with neurological diseases like aseptic meningitis and AFP.

Leveraging synthetic data to improve regional sea level predictions.

The rapid increase in sea levels driven by climate change presents serious risks to coastal communities around the globe. Traditional prediction models frequently concentrate on developed regions with extensive tide gauge networks, leaving a significant gap in data and forecasts for developing countries where the tide gauges are sparse. This study presents a novel deep learning approach that combines TimesGAN with ConvLSTM to enhance regional sea level predictions using the more widely available satellite altimetry data.